Advanced Optimization Strategies for UAV Mission Planning and Operation

Dear Colleagues,

The growing adoption of unmanned aerial vehicles (UAVs) across sectors such as logistics, environmental monitoring, disaster response, and infrastructure inspection has introduced increasingly complex operational challenges. Modern UAV operations, ranging from single-platform missions involving multiple payload deliveries to large-scale coordinated fleets, demand efficient and reliable solutions for mission planning and execution. These scenarios often require optimizing multiple interdependent objectives, including task scheduling, trajectory planning, payload management, energy consumption, and communication reliability, while operating under dynamic, uncertain, and resource-constrained environments. To address these challenges, a wide spectrum of optimization techniques have been explored, spanning exact mathematical programming, heuristic and metaheuristic algorithms, hybrid frameworks, and adaptive real-time strategies. This Special Issue focuses on recent advances in optimization methods for complex UAV operations, aiming to highlight innovative models, algorithms, and architectures that improve efficiency, scalability, and robustness. We encourage submissions that present theoretical contributions, computational frameworks, and real-world implementations demonstrating enhanced mission performance. By integrating insights from control theory, operations research, autonomous systems, and distributed decision-making, this collection seeks to advance the state of the art in UAV mission planning and foster practical solutions for next-generation aerial operations across diverse and evolving applications.

This Special Issue invites manuscripts addressing, but not limited to, the following themes:

- Mission planning and scheduling for UAV operations;

- Trajectory and path optimization;

- Payload allocation and management;

- Multi-UAV coordination and task assignment;

- Energy-efficient and resource-constrained UAV missions;

- Optimization algorithms: heuristic, metaheuristic, and hybrid methods;

- Autonomous decision-making and real-time adaptive strategies;

- Applications in logistics, environmental monitoring, and disaster response.

We look forward to receiving your original research articles and reviews.

Dr. Emanuele Luigi de Angelis
Prof. Dr. Fabrizio Giulietti
Prof. Dr. Giulio Avanzini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• unmanned aerial vehicles (UAVs)
• autonomous aerial systems
• mission planning and scheduling
• trajectory optimization
• payload allocation and optimization
• multi-UAV coordination
• optimization algorithms
• heuristic and metaheuristic methods
• energy-efficient UAV operations
• autonomous decision-making